[Tut] How to Average a List of Lists in Python?

[Tut] How to Average a List of Lists in Python? - Printable Version

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[Tut] How to Average a List of Lists in Python? - xSicKxBot - 05-07-2020

How to Average a List of Lists in Python?

Problem: You have a list of lists and you want to calculate the average of the different columns.

Example: Given the following list of lists with four rows and three columns.

Code:
data = [[0, 1, 0], [1, 1, 1], [0, 0, 0], [1, 1, 0]]

You want to have the average values of the three columns:

Code:
[average_col_1, average_col_2, average_col_3]

There are three methods that solve this problem. You can play with them in the interactive shell and read more details below:

https://repl.it/@finxter/listoflistsaverage?lite=true
Method 1: Average in Python (No Library)

A simple one-liner with list comprehension in combination with the

Code:
zip()

function on the unpacked list to transpose the list of lists does the job in Python.

Code:
data = [[0, 1, 0], [1, 1, 1], [0, 0, 0], [1, 1, 0]] # Method 1: Pure Python
res = [sum(x) / len(x) for x in zip(*data)]
print(res)
# [0.5, 0.75, 0.25]

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You can visualize the code execution and memory objects of this code in the following tool (just click “Next” to see how one step of the code unfolds).

https://pythontutor.com/iframe-embed.html#code=data%20%3D%20%5B%5B0,%201,%200%5D,%0A%20%20%20%20%20%20%20%20%5B1,%201,%201%5D,%0A%20%20%20%20%20%20%20%20%5B0,%200,%200%5D,%0A%20%20%20%20%20%20%20%20%5B1,%201,%200%5D%5D%0A%0A%0Ares%20%3D%20%5Bsum%28x%29%20/%20len%28x%29%20for%20x%20in%20zip%28*data%29%5D%0Aprint%28res%29&codeDivHeight=400&codeDivWidth=350&cumulative=false&curInstr=0&heapPrimitives=nevernest&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false

Method 2: Average with NumPy Library

You create a NumPy array out of the data and pass it to the np.average() function.

Code:
data = [[0, 1, 0], [1, 1, 1], [0, 0, 0], [1, 1, 0]] # Method 2: NumPy
import numpy as np
a = np.array(data)
res = np.average(a, axis=0)
print(res)
# [0.5 0.75 0.25]

The

Code:
axis

argument of the average function defines along which axis you want to calculate the average value. If you want to average columns, define

Code:
axis=0

. If you want to average rows, define

Code:
axis=1

. If you want to average over all values, skip this argument.

Method 3: Mean Statistics Library + Map()

Just to show you another alternative, here’s one using the

Code:
map()

function and our

Code:
zip(*data)

trick to transpose the “matrix”

Code:
data

Code:
data = [[0, 1, 0], [1, 1, 1], [0, 0, 0], [1, 1, 0]] # Method 3: Statistics + Map()
import statistics
res = map(statistics.mean, zip(*data))
print(list(res))
# [0.5, 0.75, 0.25]

The

Code:
map(function, iterable)

function applies

Code:
function

to each element in

Code:
iterable

. As an alternative, you can also use list comprehension as shown in method 1 in this tutorial. In fact, Guido van Rossum, the creator of Python and Python’s benevolent dictator for life (BDFL), prefers list comprehension over the

Code:
map()

function.

Where to Go From Here?

Enough theory, let’s get some practice!

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